A system for a multitenanted database stores data for a plurality of tenants (e.g., organizations utilizing database services). Each tenant comprises a plurality of users (e.g., company employees). The multitenanted database stores user data for each user of each tenant (e.g., name, identification number, title, salary, etc.). Tenant data is stored on a set of data partitions securely separated by tenant (e.g., on different computers, on different hard drives, on different virtual machines, etc.) in order to prevent users from accessing data belonging to other tenants. The system for a multitenanted database, comprising the large set of tenant data, has the capability to produce data analyses that would be valuable to each tenant (e.g., typical group size within organizations of different sizes, average salaries for different employee roles, etc.). Performing these data analyses requires commingling of tenant data (e.g., bringing data of different tenants together in order to analyze it as a single data set). Commingled data is transferred from the tenant data storage to a commingling storage unit and analyzed on the commingling storage unit. The data analyses can be complex operations involving big data and many computational steps, creating a problem where the commingled data server is unable to process the computational load efficiently.